The alignment of images through deformable image registration is vital to clinical
applications (eg, atlas creation, image fusion, and tumor targeting in image-guided …

Minimizing bias is critical to adoption and implementation of machine learning (ML) in
clinical practice. Systematic mathematical biases produce consistent and reproducible …

While computer vision has achieved tremendous success with multimodal encoding and
direct textual interaction with images via chat-based large language models, similar …

Self-supervised pretraining has been observed to be effective at improving feature
representations for transfer learning, leveraging large amounts of unlabelled data. This …

Transformers have rapidly gained popularity in computer vision, especially in the field of
object recognition and detection. Upon examining the outcomes of state-of-the-art object …

Medical imaging plays a crucial role in diagnosis, with radiology reports serving as vital
documentation. Automating report generation has emerged as a critical need to alleviate the …

Gastric cancer, as a malignant tumor, is one of the most common cancer-related deaths
worldwide with high mortality and incidence rates. Therefore, the endoscopic detection of …

The current study investigates the robustness of deep learning models for accurate medical
diagnosis systems with a specific focus on their ability to maintain performance in the …

Medical image analysis is crucial in modern radiological diagnostics, especially given the
exponential growth in medical imaging data. The demand for automated report generation …

Rapid and accurate classification of medical images plays an important role in medical
diagnosis. Nowadays, for medical image classification, there are some methods based on …